K means cluster

import pandas as pd

import matplotlib.pyplot as plt

import seaborn as sns

sns.set()

from sklearn.cluster import KMeans

 

raw_data = pd.read_csv('Countries_exercise.csv')

 

Remove the duplicate index column from the dataset.

data·=·raw_data.copy()

 

plt.scatter(data['Longitude'], data['Latitude'])

plt.xlim(-180,180)

plt.ylim(-90, 90)

plt.show()

 

Create a copy of that data and remove all parameters apart from Longitude and Latitude.

x = data.iloc[:,1:3]

 

Clustering

kmeans = KMeans(3)

kmeans.fit(x)

 

Clustering Results

identified_clusters = kmeans.fit_predict(x)

identified_clusters

 

data_with_clusters = data.copy()

data_with_clusters['Cluster'] = identified_clusters

data_with_clusters

 

plt.scatter(data['Longitude'], data['Latitude'],c=data_with_clusters['Cluster'], cmap = 'rainbow')

plt.xlim(-180,180)

plt.ylim(-90, 90)

plt.show()